A Grey Theory-Based Model for Regional Power Demand Forecasting and Influencing Factor Analysis

Power demand forecasting is a very important basic work in the power industry, especially for regional power demand forecasting, analysis of the factors affecting power demand, analysis of the impact of various factors on power demand. In this pap, a regional electricity demand forecasting model based on grey system theory is proposed. With GM (1,1) as the core, the NGM (1,1) model is improved on the basis of the prediction model. The forecasting results show that the fitting degree between the generated value of the power demand model and the actual value is very good, the residual analysis results are excellent and the accuracy rate reaches 99.3%. On the other hand, through the analysis of the correlation degree of various factors affecting power demand, quantify the main influencing factors, and rank the correlation degree. Finding the factors that affect the target value in the system and the main relationship between them, and grasping the characteristics of things can promote the efficient development of the system. Through modeling and calculation analysis, it shows that the prediction method used in this paper is correct, the model is scientific and reasonable, the source of model parameters is clear, the calculation process is simple, the results are easy to understand, and can clearly reflect the actual situation. It also shows that this theory has strong practical significance for the analysis of regional power demand and its related influencing factors. It provides powerful data support and quantitative analysis tools for power supply planning, macro policy regulation and construction project feasibility study.